Archive for the 'Dot Map' Category

This morning, a friend emailed me a link to this story at the Daily Mail, which contains a number of beautiful maps on America’s infrastructure networks. Go check it out; I’ll wait here while you spend fifteen minutes going “ooh!” and “ahh!” at all the images.

While they are beautiful, they are not without problems. Lovely visuals, deep conceptual errors. Let’s start with the one that stuck out to me, the visualization of job losses. At least, I assume it’s job losses. The caption at the Daily Mail reads, “Unemployment: The number of job losses in the U.S. chronicled in this stunning image.” Unemployment is different than job losses, so I’m not sure which is being mapped, but I suspect the latter.(EDIT: I’ve lately found the video that these maps come from. This is actually a map showing the distribution of manufacturing jobs in the 1990s. In the video, the dots wink out — turn black — to show the decline of the manufacturing sector. Seen at about 12 min, 50 sec in the video here: http://www.pbs.org/america-revealed/episode/4/)

A dot density map is approximately the worst way to look at a data set like this. The author(s) took the number of jobs lost in each state, converted that to a certain number of dots, and then scattered those dots all throughout the state. The result is misleading in several ways. First off, this is really a map of job loss density. The brightest areas are where the dots are clustered, which means a lot of jobs were lost in a tight space. Texas lost a lot of jobs, probably as many as Ohio or Illinois (I’m not going to count every dot, but they probably have similar numbers). But the latter two states look worse off, because they have about the same number of dots crammed into a smaller physical area. Actually, it’s not even a map of job loss density, because the areas of the states are distorted due to curvature of the Earth in this view. Washington, for example, is a lot smaller than if we were looking at it from directly above, and its unemployment picture therefore looks worse. So, this isn’t really a map of “job losses” so much as it’s a map of “job losses divided by the size of each state, if you distort the sizes of the states a lot.”

So, reading the dot concentrations will simply mislead us. But what about the number of dots? If we painstakingly counted them, we could certainly find out at least how many jobs were lost in a state without having to worry about this density issue. Well, the second big problem is that these data aren’t normalized to population. There are a lot more dots in Illinois than in Wyoming. This is because Illinois is a very populous state, whereas no one lives in Wyoming. No account was taken, seemingly, of population differences. Some states are being hit harder by the recession than others, but all you can tell from this map is that places that had more people lost more jobs. I quickly found this table prepared last year and it points out that Nevada has been hammered by the downturn, losing 8% of its jobs. Ohio, on the other hand, lost only 2.6%. But when you look at the map, which state looks worse off?

Lastly, jobs weren’t lost evenly throughout each state, so why scatter the dots evenly? Probably because the author(s) only had state-based data, but making some account for population locations would be nice. Why show a sea of lost jobs in eastern California, which is mostly desert, mountains, and unpopulated forests? The exact locations of the dots are meaningless anyway, since they’ve been distributed randomly in each state.

This map should have been a choropleth of job losses per state divided by population. It’s not nearly as sexy, but it’s also not seriously misleading.

(EDIT: As said, this critique was based on an inaccurate description of what this map is about, and I apologize for not doing my research. Much of the critique still stands — showing dots still seems odd for this data set. It’s a map of “manufacturing jobs divided by the size of each state, if you distort the sizes of the states.” The need for normalization is probably less, as well, though it couldn’t hurt.)

The dot density map was what galled me. On the other hand, my friend Chris, who sent me the link, was bothered by the map of wireless access towers:

I can’t say for certain without hearing the accompanying narration (EDIT — see below), but the author(s) very likely received a data set which had point locations for towers and broadcast power, and simply made circles proportional to the power. That’s all quite reasonable, but the map very much looks like it’s trying to portray the actual signal coverage areas, and that’s a very different thing. Most any electromagnetic signal coming from a tower is not going to move in a perfect, even circle away from the transmission point. It gets distorted by a lot of things — buildings get in the way, so do mountains and other terrain features, and the Earth’s magnetic field also affects it. And if it’s been broadcast by a directional antenna, the signal starts out stronger in some directions than others. Presenting these transmissions as circles is an overly idealized view of how they work. Even if the authors were only using circles as a symbol for power, rather than suggesting these are areas of coverage, a lot of people are going to misunderstand this as the latter. Every reader brings their own interpretations to the map, and it’s not always the one the author wants. The best you can do is try and head them off.

(EDIT: Again, I’ve now looked up the relevant section in the video to figure out what they map is actually of. It’s found at 40:20 in this video: http://www.pbs.org/america-revealed/episode/4/ — the narrator doesn’t actually say what the map is of; it just shows while he talks about how your wireless signal is bounced between towers, so I’d say the critique above stands as is. If anything, I’d say my point about misunderstanding the map is even stronger, because the program really does leave it up to you to figure out what’s going on.).

All the maps on this site have a pseudo-realistic appearance, and they’re even discussed as though you’re “seeing what the nation looks like from the skies.” My colleague Marty Elmer pointed out to me that this realism means an increased expectation of accuracy. If you’re telling me that I’m floating above the US, really seeing the job losses or broadcast signals, I’m likely to believe that this is really how things are distributed on the ground. That the signals really are circles, or the jobs really were lost in the woods of northern Michigan. I’m less likely to take the thematic data as an abstraction because the base map, with its fancy lighting effects and clouds, doesn’t look very abstracted. Generalization is not just about redrawing your linework to the right scale; it’s about credulity. This was one of the biggest points I would emphasize to my students back when I lectured on the subject. Visual abstraction needs to match data abstraction. Readers seeing a highly simplified visualization will assume the data are likewise telling a highly simplified story. If they see a very realistic and detailed basemap, they’re likely to assume that the data have been treated similarly.

In the end, we’re left with beautiful, but potentially (or sometimes outright) misleading images, and that’s a travesty. These are for a television special, and besides going in front of millions of eyes on PBS, these works will very likely go around the Internet to millions more. The maps are lovely to look at, and this means they’ll get a chance to misinform many, many more people. It’s a shame, because it’s a squandered opportunity to inform people about actual facts. Imagine pairing quality visuals with well-thought-out data treatment and map concepts, and how far that would go. But infotainment isn’t about the substance, just the style. See the headline to that Daily Mail link, for example — “Secret corpse flights,” as though this transport of bodies were illicit, rather than a routine movement of your loved ones to their desired resting place. It makes a good story, even if it’s not true.

One Nice Thing: I could go on for a long time about how excellent these look. Maps need to be beautiful if you want people to look at them and spend the time to learn something off them. I’d love to see the author(s) continue to do this great work, just with better data and ideas for portraying it.

Today’s maps come to my attention via my colleague Sam Matthews, whom I hope to get to contribute to this blog someday. He alerted me to mapsofworld.com and the wealth of intriguing and often unfortunate cartographic specimens to be found there. They have lots of material worth discussing, but for now, I’m just going to pick out a couple to highlight a problem I’ve not talked about before. Let’s start with their map of world mineral resources.

via mapsofworld.com. Click to visit.

Fairly innocuous-looking, to be sure. Tan land, blue water. Standard stuff. But if you look carefully, and you obsess about projections as I do, you’ll see that this map not only has blue water, but that it’s sitting on a blue background. That is to say, there is no distinction between the map and the background it’s drawn on. The color used on this map to mean “water” is also used for areas that are not a map. Here’s a hastily annotated copy to help explain:

A lot of people looking at this map are going to think that there’s a bunch of extra water on the planet that simply doesn’t exist. The Bering Strait between Alaska and Russia is only about 50 miles wide. Here, it looks like a huge expanse hundreds of miles across. And this map isn’t the worst of them. Here’s another one from the same site:

via mapsofworld.com. Click to visit site.

This map has an entire extra ocean added at the top, a vast unnamed and unexplored expanse beyond the Arctic Ocean, somehow more north than the North Pole itself. It’s bizarre and unnecessary, and worse, it’s misleading. If you want to know why Americans have such poor knowledge of world geography, at least a fraction of the answer lies in the above, along with all of the other carelessly assembled maps that people end up learning from.

Both of these maps could be fixed by simply inserting a neatline. A neatline is a border, usually just a black line, that separates the map from the rest of the page. The lines I have drawn in my annotated examples above are neatlines, albeit approximated. In cases like this, neatlines are the difference between “map sitting on a blue background” and “map of an alternate dimension where there are extra oceans.”

I’m actually not a fan of neatlines — I think they’re frequently unnecessary, as I argue in a post on my other blog today. While these maps would be improved by adding a neatline, they could skip it entirely by just making the page background something other than the color of the water. A bold concept, but I’m willing to promote it. Imagine: a map with blue water and a white background.

I'm going to patent this!

This phantom ocean problem issue crops up a lot with maps made using projections that aren’t rectangular, like the venerable Robinson projection above, or the Winkel Tripel. These maps have curved edges, and I suppose that bothers people who want maps to fit inside rectangles. Maybe I’m missing something. Maybe they ran a focus group and found out that people hate non-rectangular maps, or that they cause seizures or something, and that we ought to add a few extra seas here and there to fill it out.

Like most maps featured here, I can’t entirely fathom what goes on in the mapmaker’s head that makes them think it’s alright to just make up some extra water. The slogan for mapsofworld.com is “We do magic to Maps.” Maybe this is what they mean.

Critical geographers, I’m sure, could have a field day with what such maps say about people. The idea here seems to be that the landforms on the map are data, and that the oceans are merely filler, no better than the background. And it’s true, we’re a pretty land-centered species, for obvious reasons. Bodies of water are often second-class citizens on many maps, thought of only as “not-land,” or “no data.” And phantom oceans, like the above, are probably the result.

Gentle readers, our first map of the new year is one that I am finally getting to eleven months after it was brought to my attention by a reader, Matthew. It concerns a favorite subject of mine, American English dialects, and was produced by hobbyist Richard Aschmann.

Click to visit Mr. Aschmann's page on North American English dialects.

The style of this work will be familiar to those with an interest in language mapping, with boundary lines delineating different pronunciations and vocabularies. Here’s another one from the Telsur Project at the University of Pennsylvania:

Click to visit Telsur project page

While Mr. Aschmann’s work is of a conventional type, it is also by far the most complex I’ve ever seen, and therein we find the problem. There is simply too much going on in this one map to be comprehensible.

One of the primary things a map reader is going to want to do is look for spatial patterns. After all, this is quite probably the entire point of having a thematic map — showing a relationship between what happens and where it happens. If you there isn’t one, then you might as make a table, instead. Now, in the case of Mr. Aschmann’s map, there’s certainly a connection between where people live and the sorts of speech patterns that come up. The problem here, though, is that this pattern is nearly impossible to discern.

To be able to see how dialects change over space requires that you look at a certain region, determine its characteristics, then look at a second region and do the same, then a third, and so on, comparing them all along the way. Your eyes sweep across the map, and each time you take a quick read and compare with what you’ve already seen. But this only works if that read can indeed be quick. With Mr. Aschmann’s map, figuring out what’s going on in any one location is a significant chore. There are so many possible symbol types, sorting through the legend is a challenge. Just figuring out which set of lines your target area falls within can be difficult, given how many layers crop up. Even if a reader is interested only in looking up data on a single place, and not making comparisons or seeing patterns, the density makes it nearly too much trouble to be worth checking. Once you’ve successfully figured out what’s going on with one region, you can move on to the next region to compare. But by the time you’ve waded through the decoding process a second time, you’ve already forgotten what the first region means. Comparison, and therefore pattern recognition, is nearly impossible, because your brain simply can’t hold that much complexity at a time or absorb it fast enough.

Compare this with a simpler map of rainfall, below. Here, it’s easy for you to quickly spot the distribution. The color pattern is simple, and you need only look for one data set, instead of twenty. There are a couple of other reasons that this map is a bit simpler to read, as well, having to do with the symbology type, but the great majority of the difference is simply in complexity.

Grabbed from Wikimedia Commons

I understand well the urge to include multiple data sets on a map, and longtime readers may recall seeing an overly complex, multivariate map of my own on this site. The more complexity you can show, the richer the story and the more versatile the product. The map quickly begins to be more than the sum of its parts. Putting two thematic layers on a map gives you three data sets — one each for the layers, plus allowing you to visualize the relationship between the two layers. One plus one equals three. But all of this is worthless if it becomes so complex as to be unclear. A map with one clear data set is worth more than a map with fifteen data sets you can’t read. Good mapmaking is about making space intelligible — otherwise, why make a map?

This map needs to be split into a series, each of which tells its portion of the story clearly. The topic it is attempting to portray is deep and rich and complex, and any single map that attempts to encompass so much is likely to end up like Mr. Aschmann’s: uselessly dense. Not every subject can be condensed into a single visual statement, and there is no shame in breaking it down into a series of simpler points in order to clarify.

Before I leave off, I’ll also mention one other thing. This map, like so many others, is going to be even less intelligible to the millions of people out there with color vision impairments. If you happen to have standard color vision and would like to see what I’m talking about, check out Color Oracle by Bernhard Jenny.

I’ve been trying of late to focus more on major items in my critiques, rather than dealing with too many nitpicky details, in order to not repeat too many points from earlier posts. Thus, I leave discussion of the rest (such as the quality of the labeling) to you, dear readers.

One Nice Thing: Mr. Aschmann has done a valiant job of trying to ensure that everything is layered clearly, which is no small task given how many data sets are crammed in. No one data set actually obscures another. There’s still far too much going on to be useful, but it’s not impossible to pull some information out of it if you’re willing to sit down and work at it.

Today’s effort comes to me via friend and colleague Richard Donohue, who let me know about the good people of Ledge Wind Energy. You see, Ledge Wind Energy wants to build a wind farm in Brown County, Wisconsin. As part of this process, they filed many, many documents with the Wisconsin Public Service Commission, which you can read for yourself if you visit the linked site and then click on the link for Ledge Wind Energy (seems to be no way to link it directly).

Among these filings were a whole series of maps, one of which I’d like to focus on.

From Appendix W of Wisconsin Public Service Commission filing 9554-CE-100

Above is a map from Appendix W, showing the noise levels the wind farm is expected to generate. It was prepared for Ledge by Michael Theriault Acoustics, a noise control consulting firm in Maine.

Detail of noise map

This is not the most attractive cartographic product. It’s full of bright colors and high contrasts; it sits on top of a busy base map and features a cluttered, haphazard look. But why does this matter? The map gets the information across; does it matter if it’s devoid of aesthetic appeal?

Yes, yes it does. Wind power is a contentious issue, and if you look at the PSC website, you’ll note that citizens made hundreds of public comments on the proposal, many of them denouncing it. Every document that Ledge filed was scrutinized by members of the community who had to decide whether to sign on to the project or to try and stand in its way. And as they turned each page they saw maps which unfortunately looked like the above. Ledge Wind Energy has taken their community and made it look ugly. This doesn’t look like a happy future; it looks like a noisy one with garish colors. It doesn’t look like a map of a place I would want to live, and so it makes me want to oppose the company that’s trying to bring about the scenario depicted. This map is Ledge Wind Energy telling the people of Brown County that they’re going to be besieged by giant blue and purple amoebae.

It’s appearance is amateur, and that subtly makes Ledge look amateur. If they don’t take care to hire someone to make a quality map, one that’s legible (note the numbers in the image above) and isn’t unpleasant to look at, can they be trusted to put up heavy machinery in my town? Where else are they cutting corners? Companies that want to be seen as doing quality work need to do it not just in their main line of business, but in everything that’s got their name on it. All of it figures into how we assess them.

Most of the effort here was clearly devoted to the data, rather than the representation. This is raw GIS output; it’s designed more for the computer than the human. I’m sure many of the citizens of this area take pride in their community. This map’s appearance tells people that Ledge considers their homes to be points in an analysis. The land they live on, the land their ancestors lived on, is just something that needs to be fed into a computer. It’s quietly dehumanizing, which is a poor way to win people over to your vision. We’re used to maps like this, sure, so it’s not a conscious affront. But consider it in contrast to a better designed alternative that suggested the landscape is more than just data.

This map is a missed opportunity. This was Ledge’s chance to show people an attractive future. Imagine if more attention had been paid to aesthetics. Subtler colors that actually go together harmoniously. Show the noise polygons, but give them a less jarring, threatening color scheme. A cleaner, less cluttered style. Make the community look good; make the people there feel good when they see their community being represented. Ledge could have shown the people of Brown County that they care about doing quality work, that they care about being a partner in building a beautiful community. That these people are more than just numbers. Think of how few people make maps of this rural area, and how much goodwill Ledge would have generated by giving citizens a rare series of lovely maps of the places they care about. It shows knowledge of the community; an investment in it.

This map and the many others of similar quality which Ledge filed did not stay confined to the halls of government; they’ve been seen by the residents of the project area. Brown County Citizens for Responsible Wind Energy, for example, makes use of several of Ledge’s maps as part of their effort to stir up opposition to the project. Here’s their version of the noise map, to which they added a subtle Google Maps base and a few road names.

These maps are most definitely out there, and it seems like a poor marketing move to spend so little effort on the design of something that’s part of how Ledge interacts with the community.

Beyond the value of good aesthetics, a few other quick points are worth making about the noise map. First off, it has a pretty weak visual hierarchy. The noise polygons compete with the yellow dots which compete with the green parcels and the red numbers. Everything stands out equally, which means that nothing is prominent. I don’t know where to look first. No one is telling me what’s important or visually suggesting an order in which things should be read. I can’t focus on one type of data without being distracted by another. Everything screams for attention with bright colors in a sensory assault. Arranging things in a visual order, with the noise polygons being most prominent, and the houses just behind, and everything else faded into background, would help significantly.

Oddly, there are two legends on this map, and one is entirely verbal. The parcel boundaries and the green squares are described in a visual legend by the lower left corner. Below that is a written description of what the yellow dots mean and the blue and purple colors. Seems like those items ought to go into the visual legend, where people can compare what they see on the map to its meaning, rather than having to trying and imagine it based on description.

Lastly, I’ll point out that, under the noise polygons, you can’t actually tell which parcels are green and which parcels are not. It is an obvious waste of time and effort (both the mapmaker’s and the reader’s) to put data on the map and then not actually make it legible. Again, the map seems ill thought out. It looks sloppy, and this does not cast Ledge in a positive light.

I’m sure that Ledge Wind Energy asked their contractors to put together some quick technical maps on a tight budget. I do not fault the people who intended to simply generate a data visualization to answer a question for a regulatory filing. In my mind, though, Ledge missed an opportunity to help their cause by skimping on the design budget and not thinking past the data.

This map is the poster child for emotionally inappropriate symbology. A lot of people think of maps as simply carriers for data. But they do more than transmit information — they influence our thoughts and our feelings as well. They’re artwork. One point symbol is not as good as any other, and I believe that bright red and green pushpins are completely unacceptable for a map about death, and war, and terror. These are human lives we are talking about here, not regional sales numbers in a spreadsheet. This map is dehumanizing. This map makes war look tidy and fun.

The internet has brought a lot of changes to cartography. Data are cheap, distribution is cheap, and access to the technology to make maps is opening up to more and more people (though we would do well to remember that the touted geoweb revolution is still confined to the iPhone-toting wealthy western elite — click here for more of my thoughts on this). All of this is, to my mind, good stuff. But, right now, the tools are still in the formative stages. The problems with this map are not really the fault of the creator. They had a data set that they wanted to get out there and share with the world. Google provided them a free, easy to use tool to accomplish this. Ideally, better tools and better cartographic education would be available to the new influx of people interested in mapping their world, but the above shows that we’ve still got a long way to go.

And, of course, this data set is all laid on top of an unnecessary satellite photo, along with some roads that will mean nothing to most readers. But, that’s par for the course with these early days of free web maps. It is my hope that the mapmaking infrastructure will continue to improve as demand for custom mapping applications rises.

Finally, I should point out that the yellow and green pushpins are largely indistinguishable to certain types of color vision impairments.

I am glad the author made this map and shared it with the world (I am, in fact, using the data in a personal project of my own). The problems are largely forgivable and understandable. But they are still serious problems, and we need to be aware of the effects this map can have on us when we look at it.

Today we continue our trend of occasionally looking at positive, rather than negative, examples of cartography. I wanted to show off a map by Michael Bricknell, a student at the University of Wisconsin, which concerns the balloon bomb attacks on the US by Japan during the Second World War, and which recently won first prize at the Wisconsin Land Information Association’s annual conference.

Reported Balloon Bomb Incidents, by Michael Bricknell

Detail

Another detail

The colors are what really make this map, in my opinion. I am a big fan of subtle color schemes, which leave most of the crayons in the box. I think they’re easier on the eyes; they don’t shout at you with a bright rainbow that demands attention. Here, a simple palette of greys and reds goes a long way toward focusing the reader’s eyes and establishing a visual hierarchy. Imagine if this map were made with a bright blue ocean and green land and brown type — how well would the red dots stand out then? A reduced, subtle palette makes it a lot easier to bring the important information into the foreground — to create a figure-ground contrast, between what’s critical and what’s supplementary. It’s also an emotionally appropriate aesthetic, I believe. We’re dealing with topics of war and violence. Again, subdued colors fit the subject matter’s tone — bright colors would be out of place here.

The map feels a little like a 1940s intelligence report on the subject. The title typeface and the face used on the captions for each panel has a nicely militaristic feel. The greyscale, while advantageous for the other reasons mentioned above, is also very much suited to the time period. Color printing and color film were rare, and so the most of us who weren’t alive during that time tend to imagine World War II as taking place in a greyscale world.

Finally, I’ll point out the graph at the bottom. It’s quite efficient. It aligns nicely with the map of the North Pacific, and packs two graphs into one space — elevation of the balloons and the number recovered at different longitude ranges. The day/night shading is a helpful addition, as it emphasizes the sense of time better than the scale of hours along the bottom can do on its own.

In all, a worthy effort. An interesting story with a strong, coherent aesthetic behind it.

I have focused only on the positive in this post, but a more balanced treatment, positive and negative, of the work would be beneficial. In fact, when sharing his map with me, Mr. Bricknell requested constructive criticisms. In an effort to generate audience engagement, I am posing to you, the reader, a challenge (as suggested by Mr. Bricknell). Please leave comments containing your own critique of his work. I will hold back the rest of my opinions for now, to avoid unduly influencing you.

My last post generated a few comments from readers out there who disagreed with some of my assessments, and I wanted to start off today by mentioning that I appreciate hearing other people’s opinions on these things, and that I hope you will all continue to weigh in whether you agree with me or not. On further reflection, I think I was perhaps unfair in some elements of my critique last week. But, I have been ill for the past while, and so I’ll just pretend that my condition impaired my judgment. Of course, I’m still a bit ill now, but we’ll try to avoid a repeat.

Today’s map was submitted by my colleague Tim Wallace, who is responsible for naming this blog. We work in a building that also houses the Arthur Robinson Map Library, which occasionally gives away unwanted materials. Tim found this one on the free map table:

Detail. Obtained from Robinson Map Library, August 2009.

The provenance is unknown – it’s printed on thin magazine paper with a torn edge, and the reverse side contains portions of two articles which don’t identify the publication, though the corner reads “September 1979.” On the off chance you happen to know where it comes from, please write to me at cartastrophic@gmail.com.

I found the logic behind the legend confusing for a good while until I noticed the numbers. It appears that we have a map here which shows seismic risk for various tectonic plate boundaries. Red is the highest seismic potential. A fine-grain black-and-white checkered pattern is the lowest. Peach and yellow are in-between. This seems to come up every week on this blog, but I’ll say it again: if you’re showing ordered data, like high-to-low seismic potential, use an ordered set of symbols (colors, in this case). This is one reason why the legend threw me. Areas marked “Plate motion subparallel to arc” are apparently of a moderate-to-low seismic potential. But, because of the fact that they use a checkerboard pattern, and because I hadn’t the damnedest what that phrase meant, I couldn’t tell that item #4 on the legend was part of a larger scheme. This is worse than just misuse of colors; patterns are being thrown in needlessly now, too.

I could, in fact, still be reading this whole legend wrong, and reflecting poorly on the institution that agreed to award me a bachelor’s degree a few years ago. Feel free to comment if you think you’ve got a more sensible interpretation than my idea of items 1-6 being part of an ordered scheme of seismic potential.

One final note on the colors/patterns: The legend does not explain what the white bands are.

On to the point features. The symbols for successful forecast (presumably explained in the article) and active volcano are overprinted directly on top of the other colors. Look again at the colored bands. The red or yellow appear no different when they are on land vs. on water. The printer simply put these colors directly onto the white paper. But look now at those two point symbols – notice how their color changes based on whether they’re sitting on land or water or on top of something else. The printer put purple ink on top of green or blue or whatever was already there, instead of leaving a white space, as they did for the bands. Not sure what happened there, though there may be a reasonable explanation that someone more familiar with late 1970s printing technology can give. It does make the points very hard to see in some areas – I originally counted four stars, but now I can find eight. It also means that the point features shown in the legend do not match the color found on the map.

I’m hoping the magazine article makes the meaning of the Tsunami symbol clearer. Is this map showing Tsunamis that happened in the last decade? Ones happening right now? Not sure.

Note that the legend refers to various filled areas as being “sites” of earthquakes. Why are these not point features? Earthquakes have an epicenter, and move more in a circular outward fashion than a wide lateral band fashion. There may be more going on, as far as data processing goes (and, again, I wish I had the article that accompanies this), but it’s perplexing. Maybe the author(s) went with bands because it’s easier to see the bands than to dig out information out of scattered points? I’ll not be too hard on this, because it’s more mysterious than bad, without information to help understand why the map author(s) may have done this.

There are exactly two labels on the main map: Oaxaca, and Gulf of Alaska. Maybe those are both significant in the article, but it seems very strange to see just those two. They should probably be set in different type, at least, so that Oaxaca doesn’t look like the name of a sea off the Mexican coast. As a general guideline, cities and bodies of water ought to look different. One of the reasons for labeling things is to help readers who don’t already know what or where these features are. It’s entirely possible that a reader out there actually did look at this and, never having heard of Oaxaca, thought it was a water feature.

A similar problem comes up in the inset. Mexico is set in the same type as Central America. Central America is not (and was not), last I knew, a country. I’m reasonably sure Mexico is, however. But look at how they’re labeled – as though the text symbols mean the same thing in each case: country. And, of course, the tectonic plates are also set in the same type as everything else. Perhaps the mapmaker had a sponsorship deal from the makers of the typeface (I am having trouble identifying exactly which it is, on account of the scan resolution looking at the actual physical document, it appears to be Helvetica). If you are a typeface designer and want to pay me more than I deserve to use your glyphs on my maps, please contact me.

The inset would be better off having some kind of marker to show where exactly it corresponds to on the main map. Perhaps this might explain why Mexico was labeled: to help the reader locate the inset.

The water on the inset is jarring -the white makes it stand out far too much, calling your eye away from the main map. Best make it blue.

Boy, sure would be nice to have a legend to explain what’s going on with the inset. Are those blue triangles historical volcanic eruptions, or maybe earthquakes? Maybe they’re places less interesting than the Cheese Factory. And what are the little round-ish zones drawn in blue, which makes them hard to notice?

If you run this map through a filter which simulates how it might look to a person with the common red-green color vision impairment, you may notice that the green for the land and the orange for seismic potential level 2 end up looking very similar, which is rather problematic if you want to know which areas are plain land, and which areas might kill you in an earthquake.

A final reiteration of the main caveat to these criticisms – the original context for the map is missing, and the magazine article which I hope accompanied it may have helped this whole thing make more sense, and explained some things which seem out of place.

One Nice Thing: Some may disagree with me and say it’s overgeneralized, but I kind of like the simplicity of the linework. I think it works here, giving it an accessible, non-technical aesthetic. Michigan is misshapen, but I’ll live.

Another Nice Thing: Tim thinks it has a nice Schoolhouse Rock sort of feeling to it. Which is another way of getting at what I was saying above.